Abstract
This paper proposes a novel approach to generate and analyze path model by structure equation modeling (SEM). SEM is an important technique to carry out causal analysis based on path model. As such, constructing path models, which result in reliable analysis, are important in SEM. LSA-based method, which is used to build a path model from text data, is proposed. However, this method requires each document to belong to one topic; thus, the model cannot express natural variables and relationships. Therefore, this paper extends the existing approach to latent Dirichlet allocation (LDA) and generates a path model from the extracted topics by LDA. Experiments using review text data can confirm the feasibility and applicability of the proposed process.
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Acknowledgments
This research was supported by a Grant-in-Aid for Foundation of the Fusion of Science and Technology (FOST) and MEXT/JSPS KAKENHI 25240049, 25420448.
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Saga, R., Kunimoto, R. LDA-based path model construction process for structure equation modeling. Artif Life Robotics 21, 155–159 (2016). https://doi.org/10.1007/s10015-016-0270-0
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DOI: https://doi.org/10.1007/s10015-016-0270-0